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mbinois
GPareto:Gaussian Processes for Pareto Front Estimation and Optimization
Gaussian process regression models, a.k.a. Kriging models, are applied to global multi-objective optimization of black-box functions. Multi-objective Expected Improvement and Step-wise Uncertainty Reduction sequential infill criteria are available. A quantification of uncertainty on Pareto fronts is provided using conditional simulations.
Maintained by Mickael Binois. Last updated 1 years ago.
16 stars 5.96 score 38 scripts 1 dependents
cran
DiceOptim:Kriging-Based Optimization for Computer Experiments
Efficient Global Optimization (EGO) algorithm as described in "Roustant et al. (2012)" <doi:10.18637/jss.v051.i01> and adaptations for problems with noise ("Picheny and Ginsbourger, 2012") <doi:10.1016/j.csda.2013.03.018>, parallel infill, and problems with constraints.
Maintained by Victor Picheny. Last updated 4 years ago.
5 stars 2.19 score 1 dependents